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	<title>AvantGarde &#187; Industry Speak</title>
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	<description>Monthly e-Newsletter,MBA IIT Kanpur </description>
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		<title>TIPS FROM TOP- Seminar by Mr. Vikas Aggarwal(National Head Client Servicing Division, IndiaMART)</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1470</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1470#comments</comments>
		<pubDate>Mon, 29 Feb 2016 05:30:29 +0000</pubDate>
		<dc:creator>Avant Garde</dc:creator>
				<category><![CDATA[Industry Speak]]></category>

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		<description><![CDATA[On 8th January, IIT Kanpur IME Department organized a seminar on “Emerging trends, challenges and opportunities in online B2B markets” by  Mr.Vikas Aggarwal from IndiaMart.
IndiaMart is India’s largest B2B market space  with 1.5 million suppliers listed on its website, with around 10 million buyers visiting the online platform every month. Mr. Vikas Aggarwal has been a part [...]]]></description>
			<content:encoded><![CDATA[<p>On 8th January, IIT Kanpur IME Department organized a seminar on “<strong>Emerging trends, challenges and opportunities in online B2B markets</strong>” by  <strong>Mr.Vikas Aggarwal</strong> from <strong>IndiaMart</strong>.</p>
<p>IndiaMart is India’s largest B2B market space  with 1.5 million suppliers listed on its website, with around 10 million buyers visiting the online platform every month. Mr. Vikas Aggarwal has been a part of this organization since 1999 and presently heads the Client Servicing division.</p>
<p>The seminar was an interactive session where Mr. Aggarwal addressed the queries of students. He explained the difference between running a B2B business model and a B2C e-commerce model. According to Mr. Aggarwal, IndiaMart primarily plays the role of matchmaking by bringing  together buyers and sellers from different parts of the country. He explained the high importance of Data Base management and Data Analysis in the business like theirs.</p>
<p>Mr. Aggarwal explained the &#8220;freemium&#8221; model through which their business operates, that is, their basic service is free for all suppliers but to get priority based listings and other added features one had to pay a premium subscription.He shared how IndiaMart started as a website developing company for different SME’s and later decided to aggregate the same on one common platform. He also gave a brief idea about transition of business from P-Commerce (Paper) to E-Commerce (Internet, Desktop) and now to M-Commerce (Mobile) model and how Net Promoters Score (NPS) is an important factor nowadays. The case of Zappos and its acquisition by Amazon explains the importance and power of high NPS, by satisfying customer through exceptional service rather than giving discounts. He discussed how IndiaMart aims to do the same by protecting buyers from suppliers by flagging faulty suppliers and even de-listing unresponsive suppliers.</p>
<p>Apart from supplier-buyer relationship, IndiaMart believes in having a strong relationship with their employees as well. At IndiaMart they have ticket system which ensures that all kinds of employee redressals are heard and taken care of.</p>
<p>In the end he advised the students to be flexible and open minded in their career opportunities and growth as well as take care of how one is at transition in his/her career. He stressed to always strive to learn something new and try something different as one progresses in their career.Overall, it was a very informative session where the management aspirants got a glimpse in to the inner workings of India&#8217;s B2B market space.</p>
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		<title>“From Customer Surveys to Neuro meter”-Mr. Prithvi Raj (Lead, Mobile Insights: Nielsen India)</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1456</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1456#comments</comments>
		<pubDate>Mon, 29 Feb 2016 03:11:42 +0000</pubDate>
		<dc:creator>Avant Garde</dc:creator>
				<category><![CDATA[Industry Speak]]></category>

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		<description><![CDATA[On 29th January, 2016, MBA, IME Department, IIT Kanpur hosted an interactive seminar on “Advances in Consumer Research, Passive measurement, Big Data Micro segmentation and Social media listening” by Mr. Prithvi Raj, Lead-Mobile Insights, Nielsen India. The speaker began the seminar by asking questions on consumer research which the students answered enthusiastically. He updated us [...]]]></description>
			<content:encoded><![CDATA[<p>On 29th January, 2016, MBA, IME Department, IIT Kanpur hosted an interactive seminar on “Advances in Consumer Research, Passive measurement, Big Data Micro segmentation and Social media listening” by Mr. Prithvi Raj, Lead-Mobile Insights, Nielsen India. The speaker began the seminar by asking questions on consumer research which the students answered enthusiastically. He updated us with some of the steps Nielsen follows during consumer research which starts from understanding the audience,  finding the need gap, proving your product effectiveness to the people and  finally ends with sales effectiveness measurement. He also made us aware about the need of innovations, SWOT analysis and competitor analysis before launching a new product. Market research can be done without explicitly conducting surveys-by observing consumers and monitoring their online behavior. For example, Amazon shows recommendations to users by observing their online behavior.</p>
<p>The speaker also gave us insights about the consumers’ world. He mentioned some amazing facts about ways through which data is collected from users in which major contributor is Smartphone. The reason being smartphone usage says a lot about the users, his choices, interests and buying pattern. He shared with us a startling fact that an average Indian spends about 186 minutes daily on their smartphone. Surprisingly, calls contribute only 9% of the time while time spent on online activities is 52% (42% on online apps and 10% on browsing). The rest of the time is spent on games (37%) and messaging (2%). With these facts he also shared with us the concept of location based marketing which can help suggest people to set up their shops specifically in an area. The other point discussed was that brain activity can divulge a huge amount of information about an individual. Sensors and eye tracking techniques are used to understand the decisions of the consumers. Buzz on social media is analyzed to gauge the sentiments of people which companies can use to convert them to consumers. Another interesting fact was the use of smartphones to decipher what the users watch on their TV sets. Some apps capture the surrounding noise of smartphones by turning on the microphones for very short intervals. This data is referenced against a reference library which creates a  finger print and tells that at particular time which TV show is being watched by that particular user. Complete privacy is maintained in this regard. It was a very informative seminar which gave us startling facts and insights about consumer research, and different passive measurement techniques which are being used by companies.</p>
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		<title>Workshop on: “Strategic Management” &#8211; By Prof Chandra Vir Singh</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1452</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1452#comments</comments>
		<pubDate>Mon, 29 Feb 2016 02:30:40 +0000</pubDate>
		<dc:creator>Avant Garde</dc:creator>
				<category><![CDATA[Industry Speak]]></category>

		<guid isPermaLink="false">http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1452</guid>
		<description><![CDATA[IME, IIT K under the aegis of head of the department, Prof. Rahul Verman organized a 2 day workshop on strategic management by one of the distinguished adjunct faculties, Prof. Chandra Vir Singh during 6th and 7th February , 2016. Prof. Singh, an alumnus of IIT K (Department of Electrical Engineering, batch of 1968) had [...]]]></description>
			<content:encoded><![CDATA[<p style="text-align: justify;">IME, IIT K under the aegis of head of the department, Prof. Rahul Verman organized a 2 day workshop on strategic management by one of the distinguished adjunct faculties, Prof. Chandra Vir Singh during 6th and 7th February , 2016. Prof. Singh, an alumnus of IIT K (Department of Electrical Engineering, batch of 1968) had worked in TELCO , presently Tata Motors for over 40+ years. Starting his career in the domain of IT, Prof. C.V Singh headed several divisions in the domains of planning, operations,  finance, systems and so on. The workshop kick started with the initial introduction of the guest lecturer by our respected H.O.D and moved ahead with several key insights in some of the domains of strategic management. We analyzed deeply and tried to find out the key factors which play major role in creating the sustainable excellence of the successful worldwide enterprises like Ford,Boeing , Motorola, Tata Group, 3-M , General electric etc. Prof. Singh communicated that the capabilities and excellence of a successful business venture lies in the major pillars like Organizational resources, processes, values delivered and created. An organization for reaching that level of excellence as desired has to continuously evolve and convert it into a learning organization, capable of changing itself with the altering time scenarios and demands. Carrying forward, Prof. Singh also enlightened us with various excellence models which are followed across the industries, like Deming Model, Malcom Bridge Model, European Business Excellence Model and  finally Tata Business Excellence Model. With his long stint in Tata Motors, Prof. Singh has actually observed so many ups and downs of the organization in different times with respect to people, market, demands, operations, technology and so on. He also expressed some of his key understandings and learning while heading the Lucknow plant of Tata Motors. In our discussions we also touched several points on vision frameworks of an evolving organization. We touched upon issues like organizational governance, evaluation of performances<br />
of individuals and organization, CSR Frameworks, legal and ethical behaviours and so on. We also discussed the various aspects of the TBEM Models in detail to understand, what are the key essences and factors that are keeping this “Salt to Vehicle Conglomerate” a leader in several categories for decades after decades. The second day was entirely devoted to comprehend and understand the phenomenon of cross border<br />
acquisition. Prof. Singh used to be an integral part of one of the largest acquisitions happened by Tata Motors, staring from 2002-03 to acquire South Korean giant in automobiles, Daewoo Motors. He took us in a wonderful journey showcasing the various aspects of cross border acquisitions, the problems faced in terms of cultural assimilation, language, communication, organizational goals, business targets, people, process and everything. This acquisition was till date the biggest one done by any Indian company. So, naturally the challenges were also huge. He also enlightened us about the great  financial crisis that happened in 1997 and how the Asian  firms got affected by that which played a key role also behind the acquisition of Daewoo motors in Korea by TELCO. Tata Motors being a 100 % indigenous manufacturer of automobiles learned the new ways of doing things after the acquisition. In a high cost economy like South Korea (The then Asian Tiger) acquiring a company and managing its product portfolio , people and culture at a higher cost was completely an entire new learning for the group. When a company works in a high cost economy, it has to be very choosy every time in segmenting and introducing new products. With that note, Prof. Singh ended the session and workshop to think and ponder upon the facts that how a company from 3rd world economy became successful to acquire a giant like Daewoo and managing it quite effectively till date. “The key to making acquisitions is being ready because you really never know when the right big one is going to come along” &#8211; James McNerney (Chairman – Boeing). So, definitely the time, strategy and organizational<br />
motto of the Tata Motors played a key role in the successful acquisition of a company like Daewoo. The strategic management played its part everywhere, starting from the basic bidding for the company to ultimately taking on board the entire corporation with different cultures, processes and everything. The visionary management of Tata Motors was really successful in that line.<br />
By- <strong>Kinsuk Ghatak</strong></p>
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		<title>Industry Overview – Indian Retail</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1268</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1268#comments</comments>
		<pubDate>Tue, 05 Aug 2014 14:20:02 +0000</pubDate>
		<dc:creator>Avant Garde</dc:creator>
				<category><![CDATA[Alumni Speak]]></category>
		<category><![CDATA[Industry Speak]]></category>

		<guid isPermaLink="false">http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1268</guid>
		<description><![CDATA[Retail in India was always a challenge from marketers’ point of view, but the consumers are always spoilt for choice. Consumerism in India is witnessing an unprecedented growth driven by a young and working population, urbanization, rising income levels, favorable demographics as well as growing brand orientation. The Indian retail market which is estimated to [...]]]></description>
			<content:encoded><![CDATA[<p>Retail in India was always a challenge from marketers’ point of view, but the consumers are always spoilt for choice. Consumerism in India is witnessing an unprecedented growth driven by a young and working population, urbanization, rising income levels, favorable demographics as well as growing brand orientation. The Indian retail market which is estimated to be worth US$520 billion(2013) and is expected to grow at a CAGR of 13%, reflects this very well. Growing at this rate it will reach around US$950 billion by 2018. Organized retail penetration, currently estimated at 7.5%, is expected to clock a 19-20% p.a. growth to reach 10% by 2018.</p>
<p>With limited space in ‘Avant Garde’, I’ll try to throw some light on this industry through sub-topics like Industry formats prevalent in India, what goes into your purchasing at store, most common strategies that retailers adopt to maximize sales, future growth prospects, and concerns of top management. The article is based on my interactions with big Retailers like Madura Fashion &amp; Lifestyle, More Super &amp; Hypermarkets, Pantaloons Fashion &amp; Retail Ltd. etc., supported with my research on this industry.</p>
<p><strong>Retail Formats</strong></p>
<p>Let’s take a step back &amp; understand how this industry works and exciting dynamics that are prevalent. In India, the retail landscape constitute following formats –</p>
<ul>
<li><strong><em>Departmental stores</em></strong> <strong>-&gt;</strong> Westside, Shoppers Stop etc.</li>
<li><em><strong>Hypermarkets -&gt;</strong></em> Big Bazaar, Aditya Birla Retail etc.</li>
<li><strong><em>Supermarkets/Convenience stores</em><em> -</em>&gt;</strong>Aditya Birla Retail, Spencer’s etc.</li>
<li><em><strong>Specialty stores -&gt;</strong></em> Titan, Croma etc</li>
<li><em><strong>Cash &amp; Carry stores -&gt;</strong></em>Metro, Reliance etc.</li>
</ul>
<p><strong>Ever Made A Purchase At Retail Store?</strong></p>
<p>There are many teams that are constantly sweating it out to make your purchase a wonderful experience such as the following ones -</p>
<ul>
<li><em><strong>Analytics -</strong></em> There is an Analytics team that takes real time data from Point-of-sale (cash counters), several feedbacks &amp; even customers’ movement track from security cameras; and translate the data into meaningful information.</li>
<li><strong><em>Merchandiser/Category -</em></strong> These teams use this analytics to decide the merchandise to be displayed over the shelf.</li>
<li><strong><em>Buyer -</em></strong> A buyer negotiates &amp; finalizes the vendor to fulfill the supply of products.</li>
<li><em><strong>Space Planners -</strong></em> These work out the allocation of shelf space in the stores to different merchandises.</li>
<li><em><strong>Replenishment -</strong></em> These teams plan out the replenishment structure of merchandise, i.e. re-order levels, minimum order etc.</li>
<li><em><strong>Supply Chain -</strong></em> This team ensures the transfer of merchandise from warehouse, DC or vendors to respective stores at the right time &amp; with the right quantity.</li>
<li><em><strong>Operations -</strong></em> This team make sure that merchandise is available on shelf &amp; get sold to the customers.</li>
</ul>
<p><strong>Strategies Retailers Use For Sales Maximization -</strong><strong> </strong></p>
<p><em><strong>Offering discounts</strong></em></p>
<ul>
<li>Most retailers have advanced off-season sales for 15 -30 days with discounts ranging from 20-70 % on certain products</li>
<li>Higher discounts and other value added services for members</li>
</ul>
<p><em><strong>Lowering prices</strong></em></p>
<ul>
<li>Certain retailers adopt ‘First Price Right’ approach. Retailers do not offer discounts under this strategy – they directly compete on the selling price by offering a best price without any markdowns</li>
</ul>
<p><em><strong>Offering value-added services</strong></em></p>
<ul>
<li>Companies offer innovative value added services such as customer loyalty programmes, happy hours on shopping deals</li>
<li>Offers for senior citizens, contests for students, and lottery gains are now very common</li>
</ul>
<p><em><strong>Leveraging partnerships</strong></em></p>
<ul>
<li>In order to keep customers shopping for a longer time and increase conversions, retailers are now pitching to partner with manufacturers, service providers, financial companies, etc. to create a buzz around certain product categories</li>
</ul>
<p><strong> </strong></p>
<p><strong>Industry Outlook</strong></p>
<p>Organized retail market in India is burgeoning and is expected to grow at CAGR of 19-20% over the next 5 years. This will be driven by a demand, supply and also several regulatory factors which are deemed to be the future growth engines. Following are the factors that drive the growth in the Indian Retail industry: -</p>
<p><strong><em>Regulatory factors</em></strong> &#8211; Liberalization of FDI policies in retail coupled with the expected roll-out of the Goods and Service Tax</p>
<p><strong><em>Demand-side factors</em></strong> &#8211; Rising disposable income, increasing urbanization, highly aware and affluent young population, growing number of working women and changing consumer preferences</p>
<p><strong><em>Supply-side factors</em></strong> &#8211; Rapid real estate and infrastructural development, easy availability of credit, innovative physical and online channels, increased service orientation</p>
<p><strong>Top Concerns for Retailers</strong></p>
<p>Organized retailers in India have experienced rapid growth over the last decade. This growth comes along with a significant cost that has been incurred to achieve it. The returns from the business are a concern, especially with respect to the investment of time &amp; capital during its gestation period. Following are the top concerns that Retailers are anxious about: -</p>
<ul>
<li>Inventory management</li>
<li>High operating costs</li>
<li>Working capital management</li>
<li>Complex regulatory framework</li>
<li>Talent retention</li>
<li>Slowing revenue growth &amp; low retail productivity</li>
<li>Inflation</li>
<li>Inefficiencies in the supply chain</li>
<li>Achievable profitable growth</li>
</ul>
<p>Inventory management is a top concern for Retail CFOs. This is largely driven by the vagaries in the Indian supply chain such as long lead times and ordering cycles, low fill rates and lack of process orientation. These result in low turns, high inventory holding and high investment in stock.</p>
<p><strong>Retail &amp; You</strong></p>
<p><em>With this background, it is quite evident that Retail in India is a challenging industry to work for, and hence there is lot to learn from its operations. This is the best industry that help you to understand the consumer dynamism more closely and accurately. At an early stage of career, the industry let you handle good responsibilities in managing people, finance&amp; operations. Not just the internal stakeholders, it makes you well equipped to face external stakeholders as well, like vendors, regulatory authorities etc. The thick experience that you’ll gain in this industry can open avenues in FMCG and upcoming e-Commerce industries as well. </em></p>
<p><em>On the other side, as the industry grapple with thin profitability margins &amp; complex regulatory guidelines, it becomes difficult to stay motivated with all the hard work that goes with less pay structure.</em></p>
<p><em>Nevertheless it is the industry that will keep you super-charged for the rest of your life. </em></p>
<p><em>So, ready to join?</em></p>
<p><strong>References<br />
</strong></p>
<p>1. Retail report from ‘India Brand Equity Foundation (IBEF)’, March 2014 (<a href="http://www.ibef.org">www.ibef.org</a>)</p>
<p>2. ‘Pulse of Indian Retail Market &#8211; A survey of CFOs in the Indian retail sector’, March 2014 – by EY and RAI</p>
<p>3. ‘Global Power of Retailing 2014 &#8211; Retail beyond begins’, 2014 – by Deloitte</p>
<p>&#8211;</p>
<p><strong>About the Author</strong></p>
<p><strong>Vipul Mathur </strong>is an alumnus of the M.B.A. programme at I.I.T. Kanpur(Batch 2005-2007). Currently he is a <strong>Senior Manager – Supply Chain Projects (Corporate office) </strong>with<strong> Aditya Birla Group, Mumbai.</strong> Vipul has a rich experience in industries such as Retail, Textiles, Manufacturing &amp; Telecom with functional specialization in Supply Chain Management, Business Process Improvements, Strategic Projects Evaluation &amp; Commercial Excellence. Vipul is also an avid photographer with a keen interest in Digital Photography.</p>
<p><strong> </strong></p>
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		<title>Building Analytical Frameworks</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1223</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1223#comments</comments>
		<pubDate>Fri, 02 May 2014 00:28:12 +0000</pubDate>
		<dc:creator>Avant Garde</dc:creator>
				<category><![CDATA[In Focus]]></category>
		<category><![CDATA[Industry Speak]]></category>

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		<description><![CDATA[Consumers and organizations create 3.5 quintillion bytes of data daily. In fact, more than ninety percent of data in the world today has been created in the last two years. The data come from everywhere: posts on social media sites, point of sale – are only a few examples. Thanks to affordable connectivity and cloud [...]]]></description>
			<content:encoded><![CDATA[<p>Consumers and organizations create 3.5 quintillion bytes of data daily. In fact, more than ninety percent of data in the world today has been created in the last two years. The data come from everywhere: posts on social media sites, point of sale – are only a few examples. Thanks to affordable connectivity and cloud services, the world is a networked society. Today, most business organizations understand the value of collecting customer-related data. However, many struggle with the challenges of leveraging the insights from this data to create a dynamic customer relationship. They are unsure how to effectively use their customer data to make decisions that turn insights into sales growth.</p>
<p>Organizations need to deploy and use analytical strategies as a competitive differentiator and as an engine for sales growth. For this perspective, there needs to be a conceptual framework that enables organizations to implement analytical strategies for sales growth and cost reduction.</p>
<p><strong>Analytical Framework</strong></p>
<p>Most of the organizations start from stage 1 and the optimal shift for analytical strategy is obtained from stage 4. At stage 4, organizations have the capability to adopt business models that enable faster creation of value. The organization can make this shift via information sharing , stage 2, or through information responsiveness, stage 3.</p>
<p>In the first stage of the framework, the focus of the marketing organization is on tactics to better target addressable mail, like catalogs and direct mail and therefore reduce postal costs and in effect increasing profits[1]. The marketing efforts focus on segmentation efficiency and information cost reduction to reach operational efficiency. This enables the organization to gain insights from the information explosion.</p>
<p>Organizations in the second stage of the customer analytics framework share information throughout the value chain through external data and hence create a consistent customer experience over multiple channels and benefit from increased loyalty, improved sales conversion rate and better cross sell. Analytical models detect purchase “patterns” the customer has exhibited in the past and then simulate the customer segmentation. The customer analytics strategy of information sharing and the horizontal marketing approach better align the focus of a business firm with its customers’ needs[1]. </p>
<p>At stage three, the organisation develops information responsiveness through internal and external data interchange. The organizations focus on identifying the questions that – if answered – will impact their business the most. This acts as a filter on data collection and helps an organization avoid the task of collecting all sundry data and then deciding what to do with it[1]. The process of standardization adds to a major percentage of cost while analysing data. The organizations at stage 3 enhance capability of the organization from reaction to prediction.</p>
<p>In the fourth stage of the customer analytics framework, the most successful marketing organizations execute a strategy that enables information on demand and an analytics-driven approach[1]. This helps the company and customer to communicate online in real time using the customer’s preferred channel. This also enables the company in providing a personalized guided selling and customer service experience. Organizations start engaging with the customer from the point of needs identification and continue to do so throughout the buying cycle . Faster creation of value for end customer is the key focus here, there by improving direct sales.</p>
<p>Improving analytical capability is key for organizations who intend to smartly use the vast customer data they collect. Analytical capability enables organization to know their customer better and reduce the marketing and sales forces. Organizations differentiate themselves through knowledge of their customers and this is one key successful attribute of improving analytical capability. Information is a business, we are still far from quantifying this in the financial books but the time is now to use this asset for accountable business and customer communication.</p>
<p><strong>References</strong></p>
<p>1. http://www.ama-atlanta.com/files/documents/IBM-Customer-Analytics-Pay-Off.pdf</p>
<p>&#8211;<br />
Saurabh Prasad<br />
M.B.A. 2013-2015</p>
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		<title>A for Analytics in A for Advertising</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1225</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=1225#comments</comments>
		<pubDate>Thu, 01 May 2014 22:42:23 +0000</pubDate>
		<dc:creator>Avant Garde</dc:creator>
				<category><![CDATA[In Focus]]></category>
		<category><![CDATA[Industry Speak]]></category>

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		<description><![CDATA[Ever wondered how TV ads today are becoming more popular on YouTube rather than TV?  So how do we decide where to display the ads more? Thanks to analytics for gulping up most of the areas where decisions are being taken based on data available. So that we would know what we are trying [...]]]></description>
			<content:encoded><![CDATA[<p>Ever wondered how TV ads today are becoming more popular on YouTube rather than TV?  So how do we decide where to display the ads more? Thanks to analytics for gulping up most of the areas where decisions are being taken based on data available. So that we would know what we are trying to do. A consumer electronics giant was measuring how it’s TV, print, radio, and online ads function independently to drive sales by adopting new data analytics techniques. The analyses unfolded  that TV ads, after eating up 85% of the total advertising budget for one product campaign, were half as effective in prompting searches leading to purchase of product, as YouTube ads which had a 6% slice in the budget menu.  Search ads on the other hand, having just 4% of the company’s advertising budget share, generated one fourth of total sales. Playing smart and going for predictive analysis, the company, after reallocating its budget had a 9% upward lift in its sales without adding any more pennies on advertising.</p>
<p>Advertising is a newly discovered arena where data analytics is playing a major role in influencing decision making. After making such a creative ad, it’s equally important to place that ad where your consumer can not only see it but act on it at the same time. Media-mix modeling (introduced in early 1980’s) helped marketers on deciding the allocation of marketing resources by linking scanner data with advertising. Then came in digital marketing (late 1990’s) by which we have this amazing ability to monitor each and every mouse click such that we can measure the relationship of advertising and purchasing easily. For example, when a consumer (in online activities) clicks on an ad, his/her purchasing behavior is attributed to that click. When the consumer sees an ad on TV, s/he can make buying decisions instantly, but s/he can’t buy the product at that very moment. </p>
<p>But it’s not the same with online advertising. Watching the same ad on YouTube, the customer may click on it for more information, giving his/her email id and getting a mail piece from the company offering a deal. The customer may then end up visiting the store and buying the product.Data analytics thus helps the companies in making investing decisions to invest the right amount at right points in the customer –decision journey, sparking customer to act on their decisions.</p>
<p>If you are a start-up and you are looking forward to predictive analytics, bingo!  You’ve found just the right thing. Eric Siegel in his new book “Predictive Analytics,” says that it’s the power to predict who will click, buy, lie, or die.  Look at his book, predictive analytics will show you the power of data and ‘big data’ will help you with all the experience that you need to learn from.  One of the examples is very interesting. It is about predictive advertisement targeting, which is online since everyone wants to display the ad a customer is most likely to click on. It’s a win-win situation, as the customer is spared from looking at irrelevant ads.</p>
<p>It’s a new arena which is gaining momentum at a very fast rate. We need to make informed decisions that can pay us back without getting our funds wasted. Well, as stated before, we may have found just the right thing.</p>
<p><strong>References</strong></p>
<p>1. http://hbr.org/product/advertising-analytics-2-0/an/R1303C-PDF-ENG<br />
2. Predictive Analytics by Eric Segel		</p>
<p>&#8211;<br />
Pratha Pareek<br />
MBA  2013-15</p>
]]></content:encoded>
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		<title>Prof. Sunil Handa’s Laboratory in Entrepreneurial Motivation (LEM)</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=925</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=925#comments</comments>
		<pubDate>Thu, 29 Nov 2012 18:49:01 +0000</pubDate>
		<dc:creator>Mukul Joshi</dc:creator>
				<category><![CDATA[Industry Speak]]></category>
		<category><![CDATA[Entrepreneurship]]></category>
		<category><![CDATA[Intensive workshop]]></category>
		<category><![CDATA[Laboratory in Entrepreneurial Motivation]]></category>
		<category><![CDATA[LEM]]></category>
		<category><![CDATA[Prof. Sunil Handa]]></category>

		<guid isPermaLink="false">http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=925</guid>
		<description><![CDATA[“Have the end in mind and every day make sure working towards it.”
– Ryan Allis
How often have you read such lines more importantly how often have you understood the real meaning?
After the last workshop as famously known as Laboratory on Entrepreneurial Motivation (LEM), I am sure at least what the above signifies and what it stands [...]]]></description>
			<content:encoded><![CDATA[<p style="text-align: center;"><strong><em>“Have the end in mind and every day make sure working towards it.”</em></strong></p>
<p style="text-align: right;">– Ryan Allis</p>
<p>How often have you read such lines more importantly how often have you understood the real meaning?</p>
<p>After the last workshop as famously known as Laboratory on Entrepreneurial Motivation (LEM), I am sure at least what the above signifies and what it stands for in life. If you’re wondering what was so unique about this workshop. Without an iota of a doubt it was the speaker – Prof. Sunil Handa.</p>
<p><strong>Day 1</strong></p>
<p>On the day, as usual, considering it to be like yet another lectures that are organised at IIT as an intensive routine, I had hardly anticipated anything special about this one, except the fact that, I was head on with my first intensive workshop at IIT Kanpur. Entrepreneurship has always been my area of interest. But I had almost forgotten my dream of being an entrepreneur. So, at my entrepreneurial best, I left my hostel but without any real expectations. But the session turned out to be a thriller. The intense discussion, the charm of Prof. Handa and the suptuous stories, the environment was very energetic. Audience was put to imagination and the more we focussed, more we felt like entering a swamp of intellect!</p>
<p>He started the session with one of his own anecdotes.  Citing his  personal experience, he elaborated that he left his high paying  job (at  mill that he dramatically revived, and gave him 21 years of experience  in just 21 months as he proudly says) as it was continually becoming  less challenging, and he thought it was a time to move on with something  of his own and joined his brother to start their own business venture.   Further, he candidly elaborated on how on few instances he failed but  more importantly, he learnt a lot from those failures.</p>
<p>He continued to exemplify the fact that the more you work towards the  success of your own organisation the better the more will the success  bring. That is why inspite being one of the topper of his batch at IIMA,  he chose to take a road less travelled.</p>
<p>He substantiated his anecdotes and professed the idea of  entrepreneurial ideology with some concrete data. He elaborated using  basic mathematics how the companies gain more due to the appreciation of  the assets (primarily the land) rather that the actual profits  generated by the business.</p>
<p><strong>Day 2 – The LEMmers</strong></p>
<p>On day 2, we yet again got a chance to be the LEMmers – believe me it was bliss. Prof. Handa had some precise and immaculate examples (typically from his own rich experiences with the subject and a happening life) to share for every question that we shot at him and to elaborate some of his mind jolting thoughts and ideas.</p>
<p>Further, he shared some really motivating stories of his students. Now, understandably, he being an IIM Prof., has mentored many of his students to their ways to the top. Some of them are the founders of the well known companies such as Naukari.com , Fractal Analytics et al. As amusing were the stories of such start-ups, equally captivating were Prof. Handa’s  analysis of such ventures. He cleverly highlighted the parts where there was learning marked for us.</p>
<p>There were some of his remarks that I would like to share as personally I would remember them for a long time.</p>
<p><strong>1. Never jump the gun </strong></p>
<p>An entrepreneur should choose a field that he/she desire as per any criteria. But, the vital aspect is the knowledge about the sector, industry and everything even remotely related. Substantiating, Prof. Handa gave the example of his own chemical company. He joined a rigorous 2 months course, in a university in England, on microbiology just to better understand the happenings in his company. More so, he trained a group of people alongside him to have the unmatched knowledge in their field of work. <strong> </strong></p>
<p><strong>2. Always start with manageable </strong></p>
<p>This is yet another aspect that is of paramount importance, as elaborated by the Prof., and should be kept in mind while going for a venture. Prof. Handa continually stressed on the cutbacks one needs to put in place when starting a business. The reason is clear but yet is ignored by many. <strong></strong></p>
<p><strong>3. Credibility matters </strong></p>
<p>Do a venture that holds credibility. Your work ethics are the primary source of credibility and motivation for the customers as well as the employees. Believe it or not, it doesn&#8217;t take time for ill processes and frauds to leak through the walls of company or its balance sheets to reach out to the stakeholders. If you destroy the milieu that you grow in or if you do not gain respect from what you do – It is not worth doing.</p>
<p><strong>4. You can NEVER lose in business</strong></p>
<p>Last but not the least, Prof. Handa said “You can never lose in business”. Now, it certainly led to a lot of raised eye brows and, consequently, people shot a lot of queries at him. But, he embellished his statement with his comprehensive elaboration and soon made the true meaning of the statement crystal clear. If one keep eyes on the balance-sheet, market trends, customer reviews and takes rational decisions, under normal circumstances there is a little chance that you make a unrecoverable blunder.</p>
<p><strong>Bidding Adieu</strong></p>
<p>Since, it was my first hand on workshop it has set a benchmark in my mind. Prof. Handa’s own experiences and knowledge were as practical as it can get. He made us come out of our little shells and made us realise that the world is full of opportunities. We just need to put our fears and long held stereotypes behind us and work towards our goals.</p>
<p>I guess many of us also needed a push – the motivation to come out of the shell. And, as the Prof. Handa culminated his session he surely gave us that much needed reason – the head-start.</p>
<p>I end this article with a promise that I will further share the comprehensive details of experiences and the learning that we accrue when we meet Prof. Handa in Ahmadabad this December for some specific industrial visits and more!</p>
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alt="" width="157" height="182" /></p>
<p style="text-align: center;">Anil Kumar</p>
<p style="text-align: center;">MBA 2014</p>
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		<title>Pharma industry &#8211; an insight in supply chain management</title>
		<link>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=615</link>
		<comments>http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=615#comments</comments>
		<pubDate>Wed, 01 Feb 2012 16:09:13 +0000</pubDate>
		<dc:creator>Dphilip</dc:creator>
				<category><![CDATA[Industry Speak]]></category>
		<category><![CDATA[glenmark]]></category>
		<category><![CDATA[ritesh mukhoti]]></category>
		<category><![CDATA[supply chain]]></category>

		<guid isPermaLink="false">http://www.iitk.ac.in/ime/MBA_IITK/avantgarde/?p=615</guid>
		<description><![CDATA[ABSTRACT
This article explains how Pharma companies in India are coping up with ever increasing complexity of operations in the midst of strengthening regulatory and inflationary pressures. More than the time tested approaches of implementing standard SAP packages, the author explains how the real need of hour is  to be able to respond to  changes over [...]]]></description>
			<content:encoded><![CDATA[<p style="text-align: justify;">ABSTRACT</p>
<p style="text-align: justify;">This article explains how Pharma companies in India are coping up with ever increasing complexity of operations in the midst of strengthening regulatory and inflationary pressures. More than the time tested approaches of implementing standard SAP packages, the author explains how the real need of hour is  to be able to respond to  changes over and above planning.</p>
<p style="text-align: justify;">The author, Ratish Mukhoti, a Mechanical Engineer and MBA is currently working with Glenmark Pharmaceuticals as a DGM and heads the Planning function. Mr Ratish has an extensive experience in FMCG  and his previous stint in Marico as a part of Supply chain transformation project there was the main driver of service level improvement.</p>
<p style="text-align: justify;">Here he shares his experience in Pharma and describes how manufacturing, purchase and planning need to work  seamlessly for effective market- catering as well as to work for the overall company objective.</p>
<p style="text-align: justify;">The Indian Pharma industry today is in the midst of unprecedented growth with companies faced with multiple options varying from going for new molecule development, partnering with innovators for marketing rights to capturing new markets with their own, and existing formulations.  A typical mid- sized pharma company in India today can aspire for turnovers ranging from 3000- 4000 cr in topline with a value growth, close to 30% y.o.y.  With the West having wisened in the post recessionary scenario, cost and productivity seems to be the key drivers worldwide , bringing new and enhanced focus on the Supply chain, forcing it to explore  and deliver , consistent and never – before efficiencies.</p>
<p style="text-align: justify;">So, while increasing demand and growth is welcome but the way native Pharma companies are gearing up for the same is a big question. If one sees a typical setup, broadly most organizations can split their operations into two halves, the first one being called pure Generics and the latter as Branded Generics or second/ third generation generic formulations. To understand the difference, take for example a typical molecule, say Telmisartan (used against Hypertension related disorders). In highly regulated markets such as US and EU, for example, Telmisartan will be typically sold as a generic drug, meaning a Pharma chain/ large scale distributor will buy the same as a generic and market it as its own product along the chain to the end consumer ( usually through the prescription and insurance cover route). A finished formulation, however, will be given a brand name, for e.g.- Telvam and marketed through a certain warehouse- Stockist- Chemist route to the end consumer.  Herein, the objective is more of end consumer reach with the intermediates acting as inventory nodes to absorb demand fluctuations, whereas the former is more of a business chain reach. This is what is mostly seen in less regulated markets, such as in Asia, Africa and India.  Thus whereas the former is more of B2B, the latter is more of B2C, in typical Supply Chain lingo.</p>
<p style="text-align: justify;">Let us, for now, look more closely at Branded Generics/ Formulations- the second of the above case. In a standard, mid-sized setup, annual SKU variety can vary from 4000 to even 5000 plus. Monthly volumes in such cases will typically be around 2000 SKUs, with volumes of close to 50000 packs per SKU or 100 Mn units. In a standard production setup there are usually 3 different dosage forms (tablet, liquid and lotion) and thus with an even balance also 700 SKUs will be needed per dosage to form line and thus in a month of 25 working days it will be 28 changeovers or more than one changeover a day!</p>
<p style="text-align: justify;">So, for the supply chain, the key issue herein to cope with this level of variety is how can material, capacities, manufacturing times and manufacturing yield, all four fall inline with the deliveries.  There are, of course, other associated imperatives of quality and expenses, typical of any other manufacturing setup. At the outset, what is more important is to make a preliminary make vs buy decision. Apart from a cost and delivery driven, decision, in pharma, it is also a function of regulatation and licensing.  E.g., if one has to market a certain product, say in Russia and there is an existing manufacturer who is approved by Russian Health authorities to market goods there, it is best to go on third party basis with the manufacturer who has the licence and approvals. Similarly, for a company aspiring to add a product to its basket , obtaining licence from the FDA is going to be time- consuming.</p>
<p style="text-align: justify;">Going back to our issues of complexity, let us look more closely at how the pharma sector is dealing with it. There are typically two parts in the overall Supply chain planning and coordination. The first is called Master Planning of Resources and the second is called Scheduling. Typically the demand forecast comes in 2-3 months prior to the start of the actual manufacturing cycle and this is where master planning starts. So, considering the forecast and available capacities at each location, the master planning stage works out material requirements and also projects the capacity shortfall. Typically, in most companies this is worked out in an ERP package such as SAP or other software. Inputs can be directly taken from past ERP data such as expected opening inventory for each input material to arrive at net requirement or can be manually fed in, typically for capacities available, linewise which can vary from month to month. The output from such a system is a firm plan and also material requisitions which are forwarded to the procurement team, alongwith the expected delivery dates, considering the testing times. The next step is scheduling, which is active when that particular month is reached. So, based on net of previous month’s production shortfalls, how much has to be made in next one week say, daywise, and when, looking at the available material releases.</p>
<p style="text-align: justify;">So while Master Planning of resources enables the Planner to look at the long- term and broader picture, scheduling is the immediate future and at a more micro level. So, e.g., while Mater planning will project the capacity constraint in tablet manufacturing at a location depending on the bottleneck capacity, say 3 months ahead, scheduling will be more granular, stagewise breaking of tablet production into granulation, compression, coating and packing. Other key inputs will be the recipe (called formulation or BOM), product routing, i.e. how each product moves and how much time is taken for processing at each stage and alternate recipes, as applicable. So, obviously the need for ERP and other Software applications to handle this level of data and analysis arises.</p>
<p style="text-align: justify;">With all this and much higher levels of automation, where do the challenges exist now. It is firstly on the ability to handle changes. Changes can be market driven, such as market driven urgencies, it can be unexpected breakdowns, it can be delayed material availability or rejections in quality. In many cases it can also be a regulatory change calling for new artworks to be developed on the packs for a certain market. Thus the supply chain planner typically has to navigate these and replan as needed to ensure that value loss to the market and sales loss is minimized.  The second is to continuously upgrade. This upgradation may be in terms of reduced cycle times of processes, in terms of improved vendor reliability calling for lesser inventories to be maintained in the chain or it may be a more cost- effective formulation. Third, but not the last is to analyze plan vs actuals at regular buckets and translate these deviations into inputs for better future planning.  The right set of people of course will thus continue to be the backbone in the entire process.</p>
<p style="text-align: justify;">Thus there are certainly exciting days ahead for Supply chain professionals in Pharma but the key will be looking at processes rather than looking at complexities. Where are our NVA (non value adding activities) and what is the COPQ (Cost of Poor Quality). An objective, number driven, focus to drive efficiencies and control is the path ahead coupled with traditional wisdom and time- tested methodologies. Success at the end of the day will be success at the market and Supply Chain needs to be geared for that just as other teams in the organization.</p>
<p style="text-align: justify;">Contibuted By :</p>
<p style="text-align: justify;"><strong>Ratish Mukhoti</strong></p>
<p style="text-align: justify;"><strong>Deputy General Manager, Planning and Inventory Control</strong></p>
<p style="text-align: justify;"><strong>Glenmark Pharmaceuticals</strong></p>
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